ROSS co-founder Andrew Arruda wants to put the Watson-enabled legal assistant in the hands of lawyers everywhere: - This is our future, a world of collaboration and symbiotic relationships with A.I. systems. ​

Many articles about how AI is transforming the business of law chronicle how IBM's AI platform Watson beat two of Jeopardy's greatest champions back in 2011. Many go on to tell the story about how students at University of Toronto joined forces with lawyer Andrew Arruda​ to create ROSS, an artificially intelligent legal assistant (the world's first, some say) which uses Watson technology.

This blog is no different - ROSS Intelligence was one of the first companies mentioned when Legaltech.se was launched in January 2016. Back then, the fledgling NextLaw Labs and Y Combinator-funded startup was still in being taught bankruptcy law by lawyers at mega-firm Dentons. Fast forward only 16 months and ROSS Intelligence, now having branched out to other areas of the law, is employed by Sedgwick, Womble Carlyle, Bryan Cave, Baker Hostetler, Latham Watkins and a host of other firms. Another AI company, Google, tells me ROSS is the most relevant link out of 190 milllion when I search for "legal AI".

- It’s funny because our logo was created very early on and we continue to be amazed at how people took to it, and the name ROSS, says Andrew Arruda.

- I believe our current position and brand has come due to our hard work, also, we brought cutting edge AI tech from the lab to law. It is very rewarding to see how A.I.’s importance is being highlighted in other industries as well as the law, we were ahead of our time but sometimes that is not a good thing!

If you’d explain it to a lawyer who barely knows how to use a word processor: How does machine learning software differ from traditional, rule-based software?

- Rule-based software means your interaction with the system is scripted in some ways, click on a print icon, open print options, click print, etc. The system is static. Think Boolean search when doing legal research.​- With machine learning software systems are able to do things they have not explicitly been programmed to do. For example, ROSS can answer legal research questions it’s never seen before. These systems are dynamic and get better every day, says Arruda.

"It's like a full moon happening the same day you found money in an old jacket"

How much of a typical law firm’s work can be automated today? And in the future?

- There are tons of stats out there on this sort of thing but that’s not my specialty. What I will say is that it’s pretty serendipitous that advanced A.I. systems are now possible in the law as the state of the market is as competitive as ever. The tasks A.I. is good at are the tasks that clients don’t want to pay for, so in many ways, A.I. is right on time for the law.

What aI applications will we see in the future, besides document review and automation?

- Anywhere you see data retrieval-type tasks that are repetitive. Additionally, if you can find structure in a task you can teach it to a system and see how it responds and build from there. Document drafting, A.I.s assisting in client intake, etc. are all on the horizon along with some really neat systems you can build within the image recognition field.

Are law firms interested in predictive analytics for example? Can AI and predictive analytics help law firms offer fixed fees?

- Yes, predictive analytics typically revolves around the collection and organization of data in order to gain insights – A.I. can streamline this process when used in the right way. Law firms and in-house teams are working on these sorts of systems today.

Do clients demand new tools and business models? Studies indicate lack of pressure from buyers is part of the reason firms have been slow to innovate.

- Lack of pressure from buyers was a huge hindrance to legal technology in the past but the tide is continuing to turn. Demand for law firm services remains flat, clients are now refusing to pay for more and more tasks, in other words, the situation is ripe for legal technology. On top of this, advanced technology is capable of addressing some of legal's biggest problems now, so the timing is perfect. It’s like a full moon happening the same day you found money in an old jacket you hadn’t worn in a while.

Is there enough data to teach AI systems all areas of law?

- The data you need to teach AI systems comes via interactions and training at first, but then in unsupervised states, you can have the A.I. system learn on its on. The answer is neither a yes or no but an "it depends", it depends on how much training data you have and how good your A.I. infrastructure is to learn on its own – we’re lucky at ROSS to have some great partners and world-class A.I. engineers.

How do you see smaller markets, such as Sweden? Is the language barrier a big issue?

- Language is somewhat of a challenge but as NLP (natural language processing) breakthroughs continue all languages will be mapped in ways that A.I. systems can work with. The challenge for any company is really going to the largest markets first, coupled with market circumstances that are best for your product. The US legal market underwent serious changes coming out of 2008 and clients in the US have really changed things: it’s gone from a seller’s market to a buyer’s market. As I said though we will have ROSS in every country in the world, it’s all just a matter of time.​

"We are enabling lawyers to do more than ever before possible"

Should laws, contracts, and verdicts be written with machines in mind?

- Yes. I think that would help a lot when it comes to the various problems legal technology companies are solving. This being said, the engineers at ROSS love extremely hard problems so they may have another take which involves a no.

- Very clear. Look what happened with chess, after Garry Kasparov lost to deep blue a new form of chess playing was born: centaur-chess. When a human champion chess player teams up with a top-class machine system, they do not lose to a solo human/solo machine system. This is our future, a world of collaboration and symbiotic relationships with A.I. systems.

- Still have doubts? Check out what Gary Kasparovhas to sayabout A.I. these days, “intelligent machines will continue that [mechanization] process, taking over the more menial aspects of cognition and elevating our mental lives towards creativity, curiosity, beauty, and joy.”

I mean, what more should I say? Check-mate?

What does the future hold for ROSS?

- We want ROSS to be on the legal team of every lawyer in the world ushering in a new era where access to law has been democratized. Our goal has always been to build an ecosystem of A.I. tools which allow lawyers to scale their abilities in ways they never imagined, we are enabling lawyers to do more than ever before possible.